Satellite Image Classification Methods and Techniques: A Review
Sunitha Abburu,Suresh Babu Golla +1 more
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TLDR
The current research work is a study on satellite image classification methods and techniques and compares various researcher’s comparative results on satellite images classification methods.Abstract:
Satellite image classification process involves grouping the image pixel values into meaningful categories Several satellite image classification methods and techniques are available Satellite image classification methods can be broadly classified into three categories 1) automatic 2) manual and 3) hybrid All three methods have their own advantages and disadvantages Majority of the satellite image classification methods fall under first category Satellite image classification needs selection of appropriate classification method based on the requirements The current research work is a study on satellite image classification methods and techniques The research work also compares various researcher’s comparative results on satellite image classification methodsread more
Citations
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Journal ArticleDOI
Iterative Training Sample Expansion to Increase and Balance the Accuracy of Land Classification From VHR Imagery
TL;DR: Local adaptive region and boxand-whisker plot techniques are integrated into an iterative algorithm to expand the size of the training sample for selected classes in the current study and yielded the most balanced classification.
Proceedings ArticleDOI
Supervised classification of satellite images
Sayali Jog,Mrudul Dixit +1 more
TL;DR: In this paper, the performance of supervised classifiers namely minimum distance, support vector machine, maximum likelihood, and parallelepiped is evaluated on the basis of kappa coefficient and overall accuracy.
Journal ArticleDOI
A review of remotely sensed satellite image classification
Sakshi Dhingra,Dharminder Kumar +1 more
TL;DR: The focus of this study is on enhancing the classification accuracy by using proper classifiers along with the novel feature extraction techniques and pre-processing steps.
Journal ArticleDOI
A Review of Terrestrial Carbon Assessment Methods Using Geo-Spatial Technologies with Emphasis on Arid Lands
TL;DR: Geo-spatial technologies are shown to be a valuable tool for estimating carbon sequestered especially in difficult and remote areas such as arid land, and the need for further work to fill the gaps and overcome limitations in using these emerging techniques for precision carbon management is high.
References
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Journal ArticleDOI
Latent dirichlet allocation
TL;DR: This work proposes a generative model for text and other collections of discrete data that generalizes or improves on several previous models including naive Bayes/unigram, mixture of unigrams, and Hofmann's aspect model.
Proceedings Article
Latent Dirichlet Allocation
TL;DR: This paper proposed a generative model for text and other collections of discrete data that generalizes or improves on several previous models including naive Bayes/unigram, mixture of unigrams, and Hof-mann's aspect model, also known as probabilistic latent semantic indexing (pLSI).
Book
Introductory Digital Image Processing: A Remote Sensing Perspective
TL;DR: Introductory Digital Image Processing: A Remote Sensing Perspective focuses on digital image processing of aircraft- and satellite-derived, remotely sensed data for Earth resource management applications.
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